Distributed system for processing of transaction data from a plurality of gas stations

Abstract

Disclosed are methods, systems, and other implementations, including a method that includes receiving information from a plurality of retail points, with the information including transaction data for a plurality of transactions at one or more of the plurality of retail points and respective local retail data for each of the plurality of retail points. The method further includes determining for a retail point, from the plurality of the retail points, a set of promotion rules based on the transaction data and on the respective local retail data, and communicating the set to the retail point. When the set of promotion rules is applied to subsequent transaction data obtained at the retail point, a resultant promotion is generated in response to application of the set of promotion rules to one or more of the subsequent transaction data and/or to subsequent local retail data obtained at retail point.

What is claimed: 
     
         1 . A system for processing transaction data from a plurality of gas stations comprising:
 a plurality of point of sale (POS) devices each comprising:
 a processor; 
 an input device configured to receive user input indicative of selected items; and 
 a memory configured to store computer program code configured to, with the processor, cause the POS device to:
 receive an indication of at least one selected item from the input device; and 
 automatically generate transaction data indicative of the at least one selected item and local retail data; 
 
   a market intelligence (MI) server comprising:
 a server processor; and 
 a server memory configured to store server computer program code configured to, with the server processor, cause the MI server to:
 receive, in real time, transaction data from the plurality of POS devices indicative of at least one selected item and local retail data from each of the plurality of POS devices; 
 determine for at least one of the plurality of POS devices a set of promotion rules based on the at least one selected item and the local retail data from each of the plurality of POS devices; and 
 communicate, in real time, the set of promotion rules to the at least one of the plurality of POS devices, 
 
   wherein when the set of promotion rules is applied to subsequent transaction data received at the at least one of the plurality POS devices, and a promotion is generated in response to application of the set of promotion rules to one or more of the subsequent transaction data or subsequent local retail data obtained at the at least one of the plurality of POS devices, and   wherein at least one of the plurality of POS devices is remotely located from other POS devices of the plurality of POS devices and the MI server.   
     
     
         2 . The system of  claim 1 , wherein the promotion comprises at least one second item to be presented to a customer at the at least one of the plurality of POS devices in response to applying the set of promotion rules to one or more of the subsequent transaction data, including information representative of at least one first item selected by the customer from a plurality of purchasable items available at a retail point associated with the at least one of the plurality of POS devices or the subsequent local retail data obtained at the at least one of the plurality of POS devices. 
     
     
         3 . The system of  claim 2 , wherein the subsequent local retail data for the at least one of the plurality of POS devices comprises one or more of a geographic location of the at least one of the plurality of POS devices, time information, date information, the plurality of purchasable items available at a retail point associated with the at least one of the plurality of POS devices, average time between transactions completed at the at least one of the plurality of POS devices, or weather information at the at least one of the plurality of POS devices. 
     
     
         4 . The system of  claim 2 , wherein the subsequent transaction data comprises one or more of an identity of the at least one first item selected by the customer, a price of the at least one item selected by the customer, a computed average and standard deviation for the price of the at least one items selected by the customer, or a time at which the at least one first item was selected by the customer. 
     
     
         5 . The system of  claim 1 , wherein the sever memory and server computer program code are further configured to, with the server processor, cause the MI server to:
 determine for the at least one of the plurality of the POS devices the set of promotion rules comprises:   determine possible promotions presentable at the at least one of the plurality of POS devices and likelihood values for customer acceptance associated with each of the possible promotions based on the transaction data and on the respective local retail data for the each of the plurality of POS devices; and   generate the set of promotion rules based, at least in part, on the determined likelihood values of customer acceptance associated with each of the possible promotions.   
     
     
         6 . The system of  claim 5 , wherein the sever memory and server computer program code are further configured to, with the server processor, cause the MD server to:
 generate the set of promotional rules based on one or more metrics derived based on the determined likelihood values, wherein the one or more metrics include an expected revenue or an expected margin for each of the possible promotions.   
     
     
         7 . The system of  claim 5 , wherein the sever memory and server computer program code are further configured to, with the server processor, cause the MI server to:
 determine, for each of the possible promotions, at least one second item to be presented to a customer at the at least one of the plurality of POS devices in combination with at least one first item selected by the customer from a plurality of purchasable items available at a retail point associated with the at least one of the plurality of POS device, based, at least in part, on effectiveness measures that are each associated with at least one combination from a set of combinations that each includes the at least one first item to be purchased and a corresponding offer of cross-sale of at least one other item from the plurality of purchasable items available at the retail point associated with the at least one of the plurality of POS devices, each of the effectiveness measures being representative of a likelihood value that the at least one other item to be offered to the customer would be accepted when offered in combination with the at least one first item being purchased, and computed based on p=s/N, where p represents the likelihood value of the cross sale of the at least one other item when offered in combination with the at least one first item, s represents a number of successful cross sales over a period of time for the at least one other item when offered in combination with the at least one first item, and N is the number of times a cross-sale promotion offering the at least one other item in combination with the at least one first item has been presented over the period of time.   
     
     
         8 . The system of  claim 5 , wherein the sever memory and server computer program code are further configured to, with the server processor, cause the MI server to:
 derive the likelihood values for customer acceptance for each of the possible promotions based on a statistical model implemented using one or more machine-learning processes applied to the transaction data for a plurality of ‘transactions at the at least one of the plurality of POS devices and the local retail data for each of the plurality of POS devices.   
     
     
         9 . The system of  claim 8 , wherein the sever memory’ and server computer program code are further configured to, with the server processor, cause the MI server to:
 derive the likelihood values based on a statistical model generated using a support vector machine process used in conjunction with a k-nearest neighbors process applied to the transaction data for the plurality of transactions at the at least one of the plurality of POS devices and the local retail data for each of the plurality of POS devices. 
 
     
     
         10 . The system of  claim 8 , wherein the one or more machine learning processes comprise one or more of a support vector machine, a k-nearest neighbor procedure, a decision tree procedure, a random forest procedure, an artificial neural network procedure, a tensor density procedure, a regression technique, or a hidden Markov model procedure. 
     
     
         11 . The system of  claim 5 , wherein the sever memory and server computer program code are further configured to, with the server processor, cause the MI server to:
 receive, from the at least one of the plurality of POS devices, data representative of outcomes associated with promotions presented at the at least one of the plurality of POS devices over a pre-determined period of time.   
     
     
         12 . The system of  claim 1 , wherein the sever memory and server computer program code are further configured to, with the server processor, cause the MI server to:
 communicate a plurality of sets of promotional rules to the at least one of the plurality of POS devices, wherein each of the plurality of sets of promotional rules is associated with a respective time period during which the associated one of the plurality of sets of promotional rules is applied at the at least one of the plurality of POS devices.   
     
     
         13 . A market intelligence (MI) server for processing transaction data from a plurality of gas stations comprising:
 a server processor; and   a server memory configured to store server computer program code configured to, with the server processor, cause the MI server to:
 receive, in real time, transaction data from a plurality of POS devices, wherein the transaction data is indicative of the at least one selected item and local retail data from each POS device of the plurality of POS devices, wherein the at least one selected item is based on user input received from an input device associated with a respective POS device; 
 determine for at least one of the plurality of POS devices a set of promotion rules based on the at least one selected item and the local retail data from each of the plurality of POS devices; and 
 communicate, in real time, the set of promotion rules to the at least one of the plurality of POS devices, 
 wherein when the set of promotion rules is applied to subsequent transaction data received at the at least one of the plurality POS devices, and a promotion is generated in response to application of the set of promotion rules to one or more of the subsequent transaction data or subsequent local retail data obtained at the at least one of the plurality of POS devices, and 
 wherein at least one of the plurality of POS devices is remotely located from other POS devices of the plurality of POS devices and the MI server. 
   
     
     
         14 . The system of  claim 13 , wherein the promotion comprises at least one second item to be presented to a customer at the at least one of the plurality of POS devices in response to applying the set of promotion rules to one or more of the subsequent transaction data, including information representative of at least one first item selected by the customer from a plurality of purchasable items available at a retail point associated with the at least one of the plurality of POS devices or the subsequent local retail data obtained at the at least one of the plurality of POS devices. 
     
     
         15 . The system of  claim 14 , wherein the subsequent local retail data for the at least one of the plurality of POS devices comprises one or more of a geographic location of the at least one of the plurality of POS devices, time information, date information, the plurality of purchasable items available a retail point associated with at the at least one of the plurality of POS devices, average time between transactions completed at the at least one of the plurality of POS devices, or weather information at the at least one of the plurality of POS devices. 
     
     
         16 . The system of  claim 14 , wherein the subsequent transaction data comprises one or more of an identity of the at least one first item selected by the customer, a price of the at least one item selected by the customer, a computed average and standard deviation for the price of the at least one items selected by the customer, or a time at which the at least one first item was selected by the customer. 
     
     
         17 . The system of  claim 13 , wherein the sever memory and server computer program code are further configured to, with the server processor, cause the MI server to:
 determine for the at least one of the plurality of the POS devices the set of promotion rules comprises:   determine possible promotions presentable at the at least one of the plurality of POS devices and likelihood values for customer acceptance associated with each of the possible promotions based on the transaction data and on the respective local retail data for the each of the plurality of POS devices; and   generate the set of promotion rules based, at least in part, on the determined likelihood values of customer acceptance associated with each of the possible promotions.   
     
     
         18 . The system of  claim 10 , wherein the sever memory and server computer program code are further configured to, with the server processor, cause the MI server to:
 generate the set of promotional rules based on one or more metrics derived based on the determined likelihood values, wherein the one or more metrics include an expected revenue or an expected margin for each of the possible promotions.   
     
     
         19 . The system of  claim 10 , wherein the sever memory and server computer program code are further configured to, with the server processor, cause the MI server to:
 determine, for each of the possible promotions, at least one second item to be presented to a customer at the at least one of the plurality of POS devices in combination with at least one first item selected by the customer from a plurality of purchasable items available at a retail point associated with the at least one of the plurality of POS device, based, at least in part, on effectiveness measures that are each associated with at least one combination from a set of combinations that each includes the at least one first item to be purchased and a corresponding offer of cross-sale of at least one other item from the plurality of purchasable items available at the retail point associated with the at least one of the plurality of POS devices, each of the effectiveness measures being representative of a likelihood value that the at least one other item to be offered to the customer would be accepted when offered in combination with the at least one first item being purchased, and computed based on p=s/N, where p represents the likelihood value of the cross sale of the at least one other item when offered in combination with the at least one first item, s represents a number of successful cross sales over a period of time for the at least one other item when offered in combination with the at least one first item, and N is the number of times a cross-sale promotion offering the at least one other item in combination with the at least one first item has been presented over the period of time.   
     
     
         20 . The system of  claim 10 , wherein the sever memory and server computer program code are further configured to, with the server processor, cause the MI server to:
 derive the likelihood values for customer acceptance for each of the possible promotions based on a statistical model implemented using one or more machine-learning processes applied to the transaction data for a plurality of transactions at the at least one of the plurality of POS devices and the local retail data for each of the plurality of POS devices.